Workshop on Machine Learning for Cosmic-Ray Air Showers

Session

Tuesday

1 Feb 2022, 09:15

Embassy Suites by Hilton Newark Wilmington South

Conveners

Tuesday

• Frank Schroeder (University of Delaware / Karlsruhe Institute of Technology)

Tuesday

• There are no conveners in this block

Tuesday: Tuesday

• There are no conveners in this block

Tuesday: Tuesday

• There are no conveners in this block

31. Deep learning in astroparticle physics

Jonas Glombitza (RWTH AACHEN UNIVERSITY)

01/02/2022, 09:15

Talk

In the past few years, deep-learning-based algorithms have been extraordinarily successful across many domains, including computer vision, machine translation, engineering, and science. Also, in physics, applications are accumulating due to the need for fast and precise algorithms that are able to exploit huge amounts of data. So, could it even become a new paradigm for data-driven knowledge...

26. Machine Learning for High-Energy Physics Reconstruction and Analysis

Sergei Gleyzer

01/02/2022, 10:00

Talk

The Large Hadron Collider (LHC) is delivering the highest energy proton-proton collisions ever recorded in the laboratory, permitting a detailed exploration of elementary particle physics at the highest energy frontier. In this talk, I will discuss the application of machine learning to problems in high-energy physics, with a focus on the challenges associated with large, complex datasets from...

18. Exploitation of Symmetries and Domain Knowledge in Deep Learning Architectures

Mirco Huennefeld (Universität Dortmund)

01/02/2022, 11:00

Talk

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstruction tasks. Many of these applications have been adopted from other domains. However, data in the field of physics are unique in the context of machine learning, insofar as their generation process and the laws and...

7. Composition Analysis of cosmic-rays at IceCube Observatory, using Graph Neural Networks

Paras Koundal (Karlsruhe Institute of Technology)

01/02/2022, 11:45

Talk

The IceCube Neutrino Observatory, located at the South Pole, is a multi-component detector that detects high-energy particles from astrophysical sources. Cosmic Rays (CRs) are charged particles from these astrophysical accelerators. CRs and CR-induced air-showers furnish us with the possibility to discern the fundamental properties and behavior of such sources. When coupled to the IceTop...

3. Measurement of the high-energy muon multiplicity in cosmic-ray air showers with IceTop and IceCube using neural networks

Stef Verpoest (University of Gent)

01/02/2022, 14:00

Talk

The IceTop and IceCube detectors at the South Pole provide the opportunity to simultaneously measure the electromagnetic and low-energy muonic component of a cosmic-ray air shower at the surface, and the penetrating muons in the deep ice. Various properties of the bundle of muons above several 100 GeV measured in IceCube are sensitive to the mass of the primary cosmic ray and contain...

12. Air shower reconstruction using a Graph Neural Network for the IceAct telescopes

Larissa Paul (Marquette University)

01/02/2022, 14:30

Talk

The IceAct telescopes are prototype Imaging Air Cherenkov telescopes (IACTs) situated at the IceCube Neutrino Observatory at the geographic South Pole. The telescopes camera consist of 61 silicon photomultipliers  (SiPMs) with a hexagonal light guide glued to each SiPM. The IceAct telescopes measure the electromagnetic air shower component of cosmic rays in the atmosphere, which...

13. Cosmic ray mass composition study using a Random Forest applied to data from the IceAct telescopes

Larissa Paul (Marquette University)

01/02/2022, 15:00

Talk

The IceAct telescopes are prototype Imaging Air Cherenkov telescopes (IACTs) situated at the IceCube Neutrino Observatory at the geographic South Pole. The IceAct telescopes measure the electromagnetic air shower component of cosmic rays in the atmosphere, which is complementary to the muonic component measured by the IceCube in-ice detector and the particle footprint measured at the surface...

30. Pattern Recognition for Multiple Interactions in a Neutron Monitor

P.-S. Mangeard (University of Delaware)

01/02/2022, 15:15

Talk

The flux of Galactic cosmic rays at Earth is modulated by the long term magnetic variations of the Sun (11-year sunspot cycle and 22-year magnetic solar cycle). This process known as Solar modulation is most pronounced at 1 GeV and below. However, it also operates at much higher energy, still exhibiting solar magnetic polarity dependence. For the last decades, ground-based neutron monitors...

10. Composition of 100 TeV - 100 PeV Cosmic Rays with IceCube and IceTop using Boosted Decision Trees

Julian Saffer (Karlsruhe Institute of Technology)

01/02/2022, 16:00

Talk

IceTop is the surface component of the IceCube South Pole Neutrino Observatory and dedicated to the indirect detection of cosmic rays (CRs). The recent implementation of a new trigger that only requires 2 of IceTop's 6 central infill stations hit by a CR-induced air shower allowed to reduce the primary energy threshold for the detection of low-energy CRs from 1.6 PeV to 250 TeV. This lead to a...

4. Cosmic rays primary energy estimation using Machine Learning and combined reconstruction

Diana Leon Silverio (South Dakota School of Mines and Technology)

01/02/2022, 16:30

Talk

The IceCube Neutrino Observatory at the South Pole is capable of measuring two components of the cosmic rays air shower. The electromagnetic component using a km2 surface array IceTop, and the high-energy muonic component using km3 in-ice array IceCube between 1.5 and 2.5 km below the surface. The combination of both arrays in conjunction with a new flexible curvature and new timing...

1. Energy Reconstruction with Convolutional Neural Networks in IceTop

Frank McNally (Mercer University)

01/02/2022, 17:00

Talk

IceTop, the surface component of the IceCube Neutrino Observatory, consists of 81 stations that detect air showers produced by cosmic ray interactions with the atmosphere. An accurate energy estimator for IceTop is essential for studying the nature of the cosmic ray spectrum around the knee (300 TeV - 1 EeV). Using over 400,000 simulated events, we trained an array of convolutional deep neural...